00000nam 2200000za 4500 9.835931 CaOODSP 20221107150759 cr ||||||||||| 170428s2017 oncd ob f000 0 eng d CaOODSP eng eng fre n-cn--- FB3-5/2017-13E-PDF Guérin, Pierre, 1984- Markov‐switching three‐pass regression filter [electronic resource] / by Pierre Guérin, Danilo Leiva‐Leon and Massimiliano Marcellino. [Ottawa] : Bank of Canada, 2017. ii, 38 p. : col. charts Bank of Canada staff working paper, 1701-9397 ; 2017-13 "April 2017." Includes bibliographical references (p. 23-26). “We introduce a new approach for the estimation of high-dimensional factor models with regime-switching factor loadings by extending the linear three-pass regression filter to settings where parameters can vary according to Markov processes. The new method, denoted as Markov-switching three-pass regression filter (MS-3PRF), is suitable for datasets with large cross-sectional dimensions, since estimation and inference are straightforward, as opposed to existing regime-switching factor models where computational complexity limits applicability to few variables. In a Monte Carlo experiment, we study the finite sample properties of the MS-3PRF and find that it performs favourably compared with alternative modelling approaches whenever there isstructural instability in factor loadings. For empirical applications, we consider forecasting economic activity and bilateral exchange rates, finding that the MS-3PRF approach is competitive in both cases"--Abstract, p. ii. Includes abstract in French. gccst Economic forecasting gccst Statistical analysis Marcellino, Massimiliano. Leiva-Leon, Danilo. Bank of Canada. Staff working paper (Bank of Canada) 1701-9397 ; 2017-13 (CaOODSP)9.806221 PDF 3.17 MB https://publications.gc.ca/collections/collection_2017/banque-bank-canada/FB3-5-2017-13-eng.pdf